Porosity — Machine Learning-Based Prediction of Proton Conductivity in Metal-Organic Frameworks

Measurement evidence

Porosity

Machine Learning-Based Prediction of Proton Conductivity in Metal-Organic Frameworks · Han S., Lee B.G., Lim D.-W. et al. · Chemistry of Materials · 2024 · 11280-11287

1 measurement group · 4 results

Reported values remain attached to the sample, method, conditions, extraction quality and source location that produced them.

Zeo++ geometric descriptor calculation

curated 248-CIF proton-conductive MOF model/data set · Model

MOF CIFs converted to P1 structures; pore size, volume, surface area, PLD and related geometric features calculated using a 1.2 A probe.

Context
model_system
Measurement source
11283 · Machine Learning Model Construction · Table S3
PropertyReported valueNormalised valueUncertaintyOrigin and qualitySource
geometric feature count14 geometric featuresText
Exact Reported
11283 · Machine Learning Model Construction · Table S3
MOF descriptor total174SI Table
Exact Reported
S-6 · Supporting Information · Table S3
structures with PLD calculated248 MOF structuresCaption
Exact Reported
S-3 · Supporting Information · Figure S1
RAC descriptor count160 descriptorsText
Exact Reported
11283 · Machine Learning Model Construction · Table S3